Financial risk management based on quantile regression model. (18th August 2018)

• Record Type: Journal Article
• Authors: Cai, Tianming
• Is Part Of: Journal of discrete mathematical sciences & cryptography. Volume 21:Number 6(2018)
• Page Start: 1391
• Page End: 1396
• Publication Date: 2018-08-18
• Subjects: Quantile regression -- Bayesian -- VaR -- Financial market -- Nonparametric estimation; Computer science -- Mathematics -- Periodicals; Cryptography -- Periodicals; Computer science -- Mathematics; Cryptography; Periodicals; 004.0151
• DOI: 10.1080/09720529.2018.1527483
• Languages: English
• ISSNs: 0972-0529

Abstract

Abstract: To reflect the loss of asset returns in the financial market in time to better avoid risks, a quantile regression model was established. First, the development history and research background of the quantile regression model were introduced. Then, the research results of VaR method and quantile regression theory were summarized. The definition of financial risk and the Bayesian inference framework were introduced. Finally, the VaR indicators in financial risk management were introduced, and the application of Bayesian quantile regression model in the field of financial market risk management was discussed. Results show that Bayesian quantile regression had certain adaptability in the calculation of financial market VaR, and could easily calculate the VaR value under each confidence level.